Data Processing with Predictions in LoRaWAN

Abstract

In this paper, the potential to reduce the energy consumption of end devices operating in a LoRaWAN (long-range wide-area network) is studied. An increasing number of IoT components communicating over wireless networks are powered by external sources. Designers of communication systems are concerned with extending the operating time of IoT, hence the need to look for effective methods to reduce power consumption. This article proposes two algorithms to reduce the energy consumption of end devices. The first algorithm is based on the use of a measured value prediction, and the second algorithm optimizes the antenna gain of the end device. Both algorithms have been implemented and tested. The test experiments for reducing energy consumption were conducted independently for the cases with the first algorithm and then for the second algorithm. The possibilities of reducing energy consumption were also investigated for the case when both algorithms work together. The proposed predictive algorithm reduced energy consumption the least. Better results in reducing energy consumption were guaranteed by the algorithm optimizing antenna power. The greatest gain was achieved using both algorithms simultaneously. Tests of the developed algorithms, in laboratory conditions and in conditions with a change in the distance between the end device and the LoRa gateway, confirmed the possibility of reducing energy consumption during the transmission of measurement data in a low-energy wireless LoRaWAN. Reducing electric energy consumption by even a few percent for a single device can result in significant savings on a global scale.